Sonar 3D Point Cloud Object Differentiation
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Solution Overview
Problem
Conventional sonar systems struggle to differentiate objects in an underwater environment effectively, lacking the capability to provide detailed and intuitive 3D images, which limits their ability to accurately identify and track objects like fish or debris in real-time.
Innovation Solution
The development of methods and apparatuses that process sonar returns to generate a 3D matrix or point cloud, allowing for the identification and display of objects in a 3D view by determining clusters of sonar returns associated with objects, distinguishing them from the sea floor, and providing characteristics such as size, shape, and movement, enabling real-time tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sonar systems are used to detect underwater objects, then basic detection capability is provided, but the ability to differentiate objects and provide detailed 3D images is insufficient
Solution Approach 1:
The patent transitions from traditional 2D sonar displays to 3D point cloud representations by adding spatial depth information. Each sonar return is processed to extract three-dimensional coordinates (x, y, z), allowing objects to be visualized and differentiated in three-dimensional space rather than flat two-dimensional projections, significantly improving object differentiation capability
Solution Approach 2:
The patent segments the underwater environment into distinct point cloud clusters representing different objects. By grouping sonar returns into separate point clouds for each detected object and calculating individual characteristics (volume, surface area, centroid) for each cluster, the system achieves detailed object differentiation without requiring a single complex processing system
2Measurement precision
If 3D point cloud processing is implemented to generate detailed images, then object identification accuracy improves, but computational requirements increase
Solution Approach 1:
The patent processes only the necessary characteristics of point clouds (volume, surface area, centroid coordinates) rather than performing exhaustive analysis on all sonar return data. By calculating only these specific partial characteristics needed for object identification, the system achieves accurate object identification while limiting computational requirements to essential operations
Solution Approach 2:
The patent creates simplified three-dimensional representations (point clouds) that copy the essential spatial characteristics of underwater objects without requiring processing of complete raw sonar data. These point cloud models serve as simplified copies containing only the critical information needed for identification, reducing computational burden while maintaining identification accuracy
3Productivity
If real-time tracking of multiple objects is implemented, then tracking capability is provided, but the ability to provide detailed 3D information is reduced
Solution Approach 1:
The patent pre-calculates and stores essential three-dimensional characteristics (volume, surface area, centroid) for each detected object as point clouds. By having these characteristics预先 computed and stored, the system can perform real-time tracking by simply updating and comparing these pre-prepared data structures without performing complex three-dimensional reconstruction during real-time operation, thus maintaining both tracking speed and information detail
Solution Approach 2:
The patent applies different processing levels to different objects simultaneously. Each detected object receives full three-dimensional point cloud processing with detailed characteristic calculation, while the system manages multiple objects through efficient memory management and selective updating. This allows real-time tracking of multiple objects while maintaining detailed 3D information for each individual object
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables the generation of detailed 3D images of underwater environments, allowing for accurate differentiation between sea floor and objects, real-time tracking of fish, and improved computational efficiency, making it possible to display and update 3D images on low-powered devices.
Implementation Method 1
Sonar transducer elements, or simply transducers, may convert electrical energy into sound or vibrations at a particular frequency
Implementation Method 2
The transducer may receive the reflected sound (the 'sonar returns') and convert the sound energy into electrical energy
Implementation Method 3
A sonar sound beam is transmitted into and through the water and is reflected from objects it encounters
Implementation Method 4
The transducer may receive the reflected sound (the 'sonar returns')
Data Source
AI summary
A sonar system is provided including a display screen, a transducer assembly including at least one transducer that is configured to emit one or more sonar signals into an underwater environment and receive sonar return data reflected from one or more objects, and a sonar module configured to generate a 3D matrix based on the sonar return data including a plurality of sonar returns that are each defined by a 3D positional value, determine a group of the plurality of sonar returns associated with an object, assign a predetermined icon to the determined group, and generate and display 3D image of the sonar return data. The predetermined icon is positioned within the 3D image at a position that corresponds to the position of the determined group such that the position of the predetermined icon corresponds to the position of the object.